Awesome
W-Net-Keras
Unofficial implementation of W-Net for crowd counting in Keras.
Paper:
- Original_paper: Varun Kannadi Valloli, Kinal Mehta. W-Net: Reinforced U-Net for Density Map Estimation.
Results now:
On dataset ShanghaiTech B
Under development...
MAE | MSE | Mean of Frobenius Norm | MAPE | PSNR | SSIM |
---|---|---|---|---|---|
7.85 | 12.17 | 6.75e-7 | 6.46% | 29.27 | 0.93 |
Dataset:
- ShanghaiTech dataset: dropbox or Baidu Disk.
Training Parameters:
-
Loss = MSE * 1000 + BCE * 10;
-
Optimizer = Adam(lr=1e-4, decay=5e-3);
-
Batch size: 1;
-
Data augmentation: Flip horizontally online randomly;
-
Patch: No patch;
-
Batch normalization: No BN layers at present;
-
Weights: Got best weights in epoch248(250 epochs in total), and here is the loss records:
-
Prediction example:
Run:
- Download dataset;
- Data generation: run the
generate_datasets.ipynb
. - Run the
main.ipynb
to train, test, analyze and evaluate the image quality.